Treemap in Power BI is a powerful tool for displaying hierarchical and categorical data visually. Among the many Power BI charts and graphs, the Power BI Treemap Visualization stands out for its ability to compress large volumes of information into an intuitive, color-coded format. Whether you’re looking to analyze performance, compare proportions, or understand structure, the Treemap Chart in Power BI can provide insights quickly and effectively. In this blog, we’ll explore how to create a Treemap in Power BI, understand its use cases, and compare it with other data visualization tools available in Power BI. From the basics to best practices, this guide will help you learn about the Power BI Treemap Chart for business intelligence.
Table of Contents:
What is a Treemap in Power BI?
Power BI Treemap Visualization is a visual representation of data with the help of nested rectangles of different colours. Each category is represented as a tile that contains its numeric value. Subcategories can be nested within parent tiles, which helps users to get better insights.
Key Advantages of Using Treemap in Power BI
- Treemaps use space efficiently by displaying multiple data points within a compact visual area.
- A treemap is used to compare values across different categories by using tile size for comparison.
- Treemap provides Power BI Hierarchical Chart navigation that helps users to fetch information in a more detailed manner.
- Treemaps can support drill-down interactions when hierarchies are configured properly and the drill-down option is enabled.
- Treemaps use color saturation to highlight variations across another measure, such as performance or growth.
Master Power BI from scratch – Turn data into decisions like a pro!
Enroll now and build the skills the industry demands.
When to Use Treemap in Power BI?
Treemaps excel in situations where you want to show proportions in a hierarchy.
They are mainly used in cases where:
- You have numerous categories with differing and significant sizes.
- You want to compare grouped data.
- You’re reviewing multiple dimension performance (e.g., platform → genre → views).
Examples of use cases:
- Streaming platforms are analyzing views by genre.
- Retail companies are reviewing sales across categories and sub-categories.
- Marketing teams review reach by channel on campaigns.
How to Create a Treemap in Power BI (Step-by-Step)?
Let’s understand the process of creating a Power BI Treemap Chart with the help of a dataset.
| Title |
Platform |
Genre |
Views (millions) |
Release Year |
| Stranger Things |
Netflix |
Sci-Fi |
82 |
2016 |
| The Crown |
Netflix |
Drama |
45 |
2016 |
| The Boys |
Amazon Prime |
Action |
60 |
2019 |
| Wednesday |
Netflix |
Mystery |
100 |
2022 |
| The Marvellous Mrs. Maisel |
Amazon Prime |
Comedy |
35 |
2017 |
| Jack Ryan |
Amazon Prime |
Thriller |
55 |
2018 |
Step 1: Load the Dataset into Power BI
Go to the Home tab, then select ‘Get Data’ > ‘Text/CSV’ to load your dataset
After following the steps, your data will be loaded into Power BI and will appear in the Fields pane, ready for use in visualization.
This is how your dataset looks after being loaded into Power BI.
Step 2: Insert a Treemap
Click the Treemap from the Visualization pane.
This is the visualization pane in which all graphs are present.
Step 3: Drag the fields
Drag ‘Platform’ to the Group section and ‘Views’ to the Values section.
Result:
Explanation: This graph represents the Sum of Views according to the platforms.
Get 100% Hike!
Master Most in Demand Skills Now!
Top Alternatives to Treemap in Power BI
1. Bar Chart
- When to use: You want to compare Power BI Charts and Graphs side by side, such as which show had the most views.
- Why it’s good: It’s easy to read, clearly shows the values, and works without problems even if you have lots of categories.
2. Donut Chart
- When to use: You want to show how each part comprises a whole.
- Why it’s good: It’s simple, and it’s pleasing to look at when you only have a few things to compare (like Netflix versus Prime share).
3. Matrix
- When to use: If you want to visualize all your data at once, like a spreadsheet.
- Why it’s good: The Power BI Treemap Visualization provides detail and allows you to visualize different numbers simultaneously.
4. Pie Chart:
- When to use it: You have only a few things to compare and want to show a whole split up.
- Why it’s good: Simple and well-known, but only works well with Power BI Charts and Graphs.
5. Column Chart:
- When to use it: You want to show how things are changing over time or make some group comparisons.
- Why it’s good: It’s a bar chart on its side and good for spotting trends.
Power BI Treemap vs bar chart
| Feature |
Power BI Treemap Chart |
Bar Chart in Power BI |
| Visual Format |
Uses nested rectangles sized by value |
Uses horizontal or vertical bars |
| Best For |
Hierarchical data, nested categories |
Comparing single values across categories |
| Space Efficiency |
More compact; fits many categories |
Needs more space for large category counts |
| Interactivity |
Supports drill-down for deeper levels |
Limited to axis-based interaction |
| Clarity |
May become cluttered with too many items |
Clear and precise value comparison |
| Use Case Example |
Streaming views by platform → genre |
Total views per show |
Common Treemap Mistakes in Power BI (And How to Avoid Them)
- Too many categories in a Treemap can make it hard to read. To improve readability, reduce the number of categories displayed, or group similar categories together. You can also use slicers or filters to limit the data shown in the Power BI Treemap Chart.
- Using random or inconsistent colors in a Treemap can confuse users. It’s crucial to use color meaningfully to represent specific measures, such as performance, and to ensure color consistency throughout the visualization.
- Not turning on drill-down limits the ability to explore the data.
- Make sure the labels clearly describe the data represented by the tiles.
- Avoid using Treemaps for flat data structures, as they are designed to represent hierarchical relationships.
Limitations of Treemap in Power BI
- Despite being a visually compelling tool, Treemaps in Power BI come with certain constraints:
- Performance Considerations: With complex or large datasets, treemaps may take longer to load or render.
- Not Ideal for Flat Data: Treemaps are most effective with hierarchical or nested data. For flat data without structure, bar or column charts are better suited.
- Difficult to Interpret with Many Categories: When there are too many small tiles, it becomes hard to distinguish and read the content.
- Limited Labeling: Labels can become unreadable in smaller rectangles, especially if the font size is auto-adjusted.
- Overuse of Color: If not used thoughtfully, color saturation may confuse rather than clarify the insight.
Best Practices for Designing Treemaps in Power BI
- Reduce categories to eliminate data chaos and ease readability.
- Use colors wisely and consistently to convey grouping in your Treemap Chart in Power BI data.
- Make sure your labels are readable. Avoid having font sizes too small in the tiles.
- Use tooltips and drill down to encourage interaction and further data consideration.
- Treemaps are one of the advanced data visualization tools within Power BI.
Real-World Treemap Use Cases
1. Visualizing Hierarchical Data
Treemaps are ideal for representing data with multiple levels of hierarchy. For example, in a business context, you can break down revenue by region → country → product category, helping users understand how each sub-level contributes to the whole.
2. Comparing Proportions Between Categories
Treemaps use tile size to represent values, making it easy to compare different categories at a glance. This is helpful when analyzing how one segment performs relative to others, such as total sales by department or views by genre.
3. Identifying Dominant Segments Quickly
With color and size encoding, treemaps immediately highlight which segments dominate. For example, in a marketing dashboard, you can see which campaign or channel generated the highest engagement without reading detailed numbers.
4. Efficient Use of Dashboard Space
Treemaps are compact and display a large amount of information in a small visual area. This makes them useful when dashboard space is limited, but you still need to present multiple data points.
5. Enabling Interactive Data Exploration
Treemaps in Power BI support drill-down and tooltips, allowing users to explore deeper layers of data. For instance, clicking on a platform tile can reveal performance by genre or show, making it useful for guided data analysis.
Conclusion
Power BI Treemap Visualization is a highly effective way to visualize complex, hierarchical data. It helps users quickly identify trends, compare proportions, and interact with insights using drill-down features. While not suited for every dataset, the Power BI Treemap Chart stands out among data visualization tools for its compactness and clarity. By understanding its strengths and limitations, you can better decide when and how to use the Power BI Treemap Visualization in your reports and dashboards.
To learn more about Power BI and its functions, check out this Power BI Course and also explore Power BI Interview Questions prepared by industry experts.
Treemap in Power BI- FAQs
Q1. What is a Treemap in Power BI?
A Treemap is a visual provided by Power BI to show nested rectangles representing hierarchical data.
Q2. When should I use a Treemap?
You can use a treemap when you need to show relationships within a hierarchy.
Q3. Can Treemaps show percentages?
Yes, Treemaps can show percentages by using data labels or tooltips to display each category’s share of the total.
Q4. Can I drill down in a Treemap?
Yes, you can drill down in a Treemap to explore deeper levels of hierarchical data.
Q5. Do Treemaps work well with time-series data?
No, Treemaps don’t work well for time-based data as they show categories, not changes over time.
Q6. How to use Treemap in Power BI?
To use a Treemap in Power BI, select the Treemap visual, then drag a categorical field to Group and a numeric field to Values to display hierarchical data as nested rectangles.